Comparative analysis shows deep learning improves object detection and decision-making in autonomous vehicles, suggesting a shift from traditional methods.
Key Points
Deep learning enhances safety and decision-making in autonomous vehicles, improving overall functionality and adaptability.
The study employed models like LSTM and DNNs, achieving significant advancements in object detection and trajectory prediction.
Observational analysis integrated reinforcement learning for adaptive decision-making, ensuring responsiveness in dynamic environments.
This work highlights the potential for safe and efficient autonomous vehicle systems using advanced AI techniques and sensor fusion.